On Tuesday, the White House Office of Science and Technology Policy (OSTP) released a report entitled “Science: A New Golden Age,” in which it lays out how it has viewed science, found it lacking, and believes the Trump administration is in the perfect position to fix things. It’s a bit unexpected coming from an administration that has been proposing crippling funding cuts to research and trying to enable political appointees to terminate grants awarded based on scientific merit.
The report presents itself as the spiritual successor of “Science, the Endless Frontier,” a policy document that laid out the case for government-funded science in the wake of World War II. The New Golden Age (SNGA) says that, while the concepts promoted by the original remain vital, the circumstances have changed such that we need major revisions to how the government is implementing things.
The result is an odd mix. It completely ignores or glosses over many things that the administration is doing to harm scientific progress. In some cases, it identifies issues that have already been discussed as problems within the scientific community. Elsewhere, it’s a mixture of political grievances, ideas without a solid intellectual foundation, and an injection of Silicon Valley’s perspective on innovation (Michael Kratsios, the director of the OSTP, formerly worked with Peter Thiel). As a result, it’s unlikely to have anything like the impact of “Science, the Endless Frontier.”
Lacking internal coherence
The report is trying to make the case that US government-funded science has some structural problems, serious enough that they require major changes to the entire enterprise. (It also makes a positive argument, namely that developments in AI necessitate a new approach, which we’ll come back to.) Some of those concerns are real and had been discussed within the research community previously.
One of the real problems it discusses is the amount of time researchers need to spend on writing grants and performing administrative tasks, taking away from their time doing research. SNGA promises to relieve this by simplifying regulations and streamlining the grant application process. But it’s also remarkably vague, in that its authors do not identify a single regulation that is in need of reform.
The report also seems not to realize that it is being written by the Trump administration. One of the reasons researchers have spent so much time writing grants is a general uncertainty about funding, and that’s something that the administration has dramatically increased through the haphazard termination of existing grants, by proposing massive budget cuts for science agencies, and by slowing the release of funds that had been allocated to researchers by Congress.
This lack of self-awareness permeates the document, but it’s worth looking at a second example. In several instances, the report highlights the Human Genome Project as an example of the sort of project that government excels at driving. But it seems to be unaware that the project was a major international collaboration, with entire chromosomes being sequenced outside the US. Pride in the completion of the genome seems out of place from an administration that is actively trying to minimize international collaborations involving the researchers it funds.
In the same way, it highlights how the Human Genome Project required the immediate and open release of the data it generated as an example of what the Trump administration considers “gold standard science.” But SGNA also decries how making results accessible to all has allowed other countries to develop industries based on advances that occurred within the US.
In short, the report lacks a perspective that’s internally coherent, or consistent with the other goals and actions of the Trump administration.
The role of innovation
Another area of concern in the SGNA is that of innovation, both within science and in the translation of scientific findings to commercialization. The former has been recognized as a potential issue by the scientific community, as some measures indicate that more of the research we’re doing in recent decades is incremental, and there are fewer large advances. The challenge is that these measures are controversial; it’s hard to reach consensus on what counts as innovative, and some impacts of research may take longer to become apparent than most studies of the issue consider.
Yet the SGNA treats this as settled and uncontroversial. It talks a lot about how we need to promote more innovative science, and suggests a wide range of different funding models that might promote more innovation. It also says agencies will need to evaluate whether grant funding is accomplishing what we intend it to. But it never describes how agencies should objectively measure innovativeness, so it’s unclear how they can perform that evaluation, or whether the scientific community will consider their results valid.
On the flipside, this is one of the cases where SNGA’s proposed solutions align with Trump administration actions, specifically its call to reduce the importance of peer review. In the new document, peer review is presented as part of the problem: “Review panels often gatekeep proposals by consensus, disincentivizing transformative ideas.” And many of the new funding mechanisms it proposes include reviews by single individuals who may or may not be trained scientists. While this is likely to broaden the scope of ideas that get funded, it also seems likely that it will increase the funding of fringe ideas, something that the OSTP does not seem to consider.
(I’ll note that this is consistent with Trump administration actions and not ideas; peer review remains part of what the administration is calling gold standard science, which SNGA also endorses.)
Aside from innovations within science, SNGA also is concerned with how science gets translated into products and processes by commercial interests. Here, the report decries what it terms a linear model, one where government funds basic science, which the market then takes a one way journey to commercialization. Again, this is a case where people in science would likely agree that things are often considerably more complex. The report favors a model where commercialization is more of a conversation, as technology developments allow new scientific work that in turn leads to new or enhanced opportunities for further commercialization.
There have definitely been instances of this. A great example is the real-time RT-PCR tests that were initially used during the pandemic. Commercialization of both reverse transcriptase (the RT) and PCR allowed scientists to develop the real-time monitoring of reaction progress for their own research. Companies then commercialized hardware that simplified the process, and still other companies then developed diagnostic tests using it.
But SNGA puts all of its eggs in that basket, which is just as incomplete as the linear model. Quantum mechanics stayed trapped in physics departments for roughly 50 years before it got commercialized via lasers and semiconductors. And it’s hard to imagine the timeline in which we’ll end up commercializing something like the detection of gravitational waves.
The whole idea of government funding for basic science was the recognition that it’s possible to predict in advance which scientific findings will have commercial applications, so companies, for the most part, weren’t going to do it. While SNGA is right that we should encourage those cycles of science-technology innovation when we find them, it offers no suggestions for how we identify one before it takes off and government funding becomes irrelevant. Because that is the only type of technology development it acknowledges exists, it has little to offer for any others.
Innovation in action?
Perhaps the strangest thing about SNGA is that it seems upset that scientists are highly trained specialists (although that’s in keeping with the Trump budget proposals, which radically slash funds for graduate students). At its most extreme, it presents people in the field as out-of-touch elitists. “Engineering students study the theory of combustion, but few can disassemble and rebuild a combustion engine,” its authors complain. “Graduate programs reward theoretical contributions measured in citation counts, but not practical applications measured in jobs and dollars.”
Here, its solution is grand in scope. It views the maker community, which is mostly interested in scratching personal itches, as a sign that the US public wants to make things again. The SNGA authors figure that they would be perfectly happy making things for science. “Establish national fellowships for skilled craftspeople,” they suggest, “practitioner-in-residence programs embedding machinists and technicians alongside Ph.D. researchers, and portable industry-recognized credentials in advanced manufacturing and lab techniques.”
It’s unclear what these machinists will be doing with the researchers. But the results will be glorious: “By rebuilding the link between science and hands-on craft, federal leadership can ensure that the economic returns of discovery, including the jobs, supplier networks, and process knowledge encoded in the hands of workers, accrue to Americans.”
Its example is Detroit in its heyday, although that seems to have been a period of engineering refinements that lacked a notable scientific component. And it’s unclear what scientific research center the SNGA associates with that time.
Are there some fields that can be revolutionized by things like a 3D printer and a bit of time with the maker community? Robotics seems like an obvious choice; developmental biology does not.
Elsewhere, the report returns to the familiar claim that regulations are also stifling the potential for science-driven commercial innovation. The only specific area that’s cited, however, is nuclear power: “nuclear energy stalled in America not because the physics failed, but because regulatory choices over the past half-century made building uneconomical.” That is not a realistic reading of the history, as there is little indication that regulations are the primary cause of the massive delays and cost overruns that plague nuclear plant construction.
Political grievance and Silicon Valley
The complaints about regulations are one of the many cases where SNGA descends into political and cultural grievance. The most obvious case is where it detours to grumble about the role of the scientific community in the arguments over COVID school closures, but there are many additional ones.
It is once again dismissive of diversity, equity, and inclusion (DEI), while saying that all Americans with aptitude need to have access to scientific training—exactly what DEI programs were meant to ensure. It also complains that foreign students were taking slots in PhD programs from deserving Americans, while ignoring the reality that the administration’s attacks on science funding have caused a number of schools to cut the number of students they admit. The fact that those foreign students often want to stay in the US to contribute to either scientific or commercial endeavors is also ignored.
Grant overheads allow the institutions that host federally funded research to pay for the upkeep of the facilities where science happens. But they’ve been targeted by the administration, so the SNGA takes time to complain about them as well.
Most strikingly, the administration that terminated grants wholesale due to political disagreements with the subjects they were funding had the audacity to argue that it would lead the charge to “ensure that selection [of grants] rests purely on merit, not the political fashions of the day.”
Beyond the political grievances, the report seems to have been shaped by OSTP head Kratsios’ time as a venture capitalist. Venture capital is presented as a separate source of scientific funding from government and commercial. SNGA presents it as potentially more rigorous, since companies will fail if they’re based on faulty scientific ideas. Left out is a consideration of the fact that most venture-backed companies do in fact fold; this is a track record that would be considered problematic by the authors of this report if it involved grant-backed projects.
This attitude pervades the report’s approach to AI, which largely buys into the biggest hype imaginable. The reality is that we’re still in the process of understanding what types of AI developments will have an impact in which fields. But SNGA envisions a future that, well, deserves to be read in full:
These pieces lay the foundation for a continuous, market-mediated, agent-based scientific economy. Imagine a funder posting a million-dollar bounty for the first validated therapeutic target for a rare disease. An agent working on adjacent problems notices a promising lead and posts a smaller bounty for replicating the finding. Other agents assess whether the problem falls within their competence, bid for the work, and contract an autonomous laboratory accessible through the internet, which runs the experiment and returns cryptographically signed results.
I guess we all have our dreams.
But it’s not clear what dream the people who wrote the new report are pursuing. The Endless Frontier was a serious effort to make the case that it was in the US’s national interest to fund basic science, even if there wasn’t a clear commercial or national security endpoint to the work. Its audience was the policymakers that could turn that into a reality.
A New Golden Age, in contrast, is a grab bag of political grievances, half-thought-through justifications for policies the Trump administration was already pursuing, and insinuations that scientific experts are kind of annoying and should learn how to fix car engines. It’s unclear who the report’s audience is. Certainly not the policymakers in the current administration, since it repeatedly indicates that the decisions they are making are great already. And it’s certainly not the scientists, who are currently suffering from the impact of those decisions.
A similar ambiguity exists about the goals of the document. There are lots of specific suggestions: get new funding mechanisms; don’t pay attention to peer review; hire some mechanics; get industry more involved; support AI, as it will change everything. But if those added up to a coherent whole, I was not able to identify it.
“A decade from now, American researchers should look back at our work and say: ‘The vital questions I could not pursue then, I am free to pursue now,’” Kratsios wrote about the document, in what seems to be the clearest indication of a goal. But A New Golden Age provides no reason to expect that they will.
